RedwineAnalysis
Suchismitha Vedala
6/16/2018
Project Description
This is a red wine data analysis project. In this project, we analyse what chemical feature impacts the quality of the red wine.
Peforming Initial Data Analysis
## [1] "fixed.acidity" "volatile.acidity" "citric.acid"
## [4] "residual.sugar" "chlorides" "free.sulfur.dioxide"
## [7] "total.sulfur.dioxide" "density" "pH"
## [10] "sulphates" "alcohol" "quality"## [1] 1599 12The data has 1599 rows and 12 columns
The structure of the data is as follows:
## 'data.frame': 1599 obs. of 12 variables:
## $ fixed.acidity : num 7.4 7.8 7.8 11.2 7.4 7.4 7.9 7.3 7.8 7.5 ...
## $ volatile.acidity : num 0.7 0.88 0.76 0.28 0.7 0.66 0.6 0.65 0.58 0.5 ...
## $ citric.acid : num 0 0 0.04 0.56 0 0 0.06 0 0.02 0.36 ...
## $ residual.sugar : num 1.9 2.6 2.3 1.9 1.9 1.8 1.6 1.2 2 6.1 ...
## $ chlorides : num 0.076 0.098 0.092 0.075 0.076 0.075 0.069 0.065 0.073 0.071 ...
## $ free.sulfur.dioxide : num 11 25 15 17 11 13 15 15 9 17 ...
## $ total.sulfur.dioxide: num 34 67 54 60 34 40 59 21 18 102 ...
## $ density : num 0.998 0.997 0.997 0.998 0.998 ...
## $ pH : num 3.51 3.2 3.26 3.16 3.51 3.51 3.3 3.39 3.36 3.35 ...
## $ sulphates : num 0.56 0.68 0.65 0.58 0.56 0.56 0.46 0.47 0.57 0.8 ...
## $ alcohol : num 9.4 9.8 9.8 9.8 9.4 9.4 9.4 10 9.5 10.5 ...
## $ quality : int 5 5 5 6 5 5 5 7 7 5 ...The summary statistics of the data are as follows:
## fixed.acidity volatile.acidity citric.acid residual.sugar
## Min. : 4.60 Min. :0.1200 Min. :0.000 Min. : 0.900
## 1st Qu.: 7.10 1st Qu.:0.3900 1st Qu.:0.090 1st Qu.: 1.900
## Median : 7.90 Median :0.5200 Median :0.260 Median : 2.200
## Mean : 8.32 Mean :0.5278 Mean :0.271 Mean : 2.539
## 3rd Qu.: 9.20 3rd Qu.:0.6400 3rd Qu.:0.420 3rd Qu.: 2.600
## Max. :15.90 Max. :1.5800 Max. :1.000 Max. :15.500
## chlorides free.sulfur.dioxide total.sulfur.dioxide
## Min. :0.01200 Min. : 1.00 Min. : 6.00
## 1st Qu.:0.07000 1st Qu.: 7.00 1st Qu.: 22.00
## Median :0.07900 Median :14.00 Median : 38.00
## Mean :0.08747 Mean :15.87 Mean : 46.47
## 3rd Qu.:0.09000 3rd Qu.:21.00 3rd Qu.: 62.00
## Max. :0.61100 Max. :72.00 Max. :289.00
## density pH sulphates alcohol
## Min. :0.9901 Min. :2.740 Min. :0.3300 Min. : 8.40
## 1st Qu.:0.9956 1st Qu.:3.210 1st Qu.:0.5500 1st Qu.: 9.50
## Median :0.9968 Median :3.310 Median :0.6200 Median :10.20
## Mean :0.9967 Mean :3.311 Mean :0.6581 Mean :10.42
## 3rd Qu.:0.9978 3rd Qu.:3.400 3rd Qu.:0.7300 3rd Qu.:11.10
## Max. :1.0037 Max. :4.010 Max. :2.0000 Max. :14.90
## quality
## Min. :3.000
## 1st Qu.:5.000
## Median :6.000
## Mean :5.636
## 3rd Qu.:6.000
## Max. :8.000We observe that there are 11 characteristics which effect the quality. We will perform analysis to # Univariate Plots Section
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 3.000 5.000 6.000 5.636 6.000 8.000
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 2.740 3.210 3.310 3.311 3.400 4.010
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 4.60 7.10 7.90 8.32 9.20 15.90
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.1200 0.3900 0.5200 0.5278 0.6400 1.5800
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.000 0.090 0.260 0.271 0.420 1.000
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.9901 0.9956 0.9968 0.9967 0.9978 1.0037
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.01200 0.07000 0.07900 0.08747 0.09000 0.61100
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.900 1.900 2.200 2.539 2.600 15.500
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1.00 7.00 14.00 15.87 21.00 72.00
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 6.00 22.00 38.00 46.47 62.00 289.00
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.3300 0.5500 0.6200 0.6581 0.7300 2.0000
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.40 9.50 10.20 10.42 11.10 14.90
Univariate Analysis
After performing initial and univariate analysis, now we answer some of the important questions that gives an idea of the data and helps us make further analys
What is the structure of your dataset?
The data consists of 1599 observations and 12 characteristics. 11 characteristic fearures and 1 impacting feauture Quality.
What is/are the main feature(s) of interest in your dataset?
Quality is of main interest in the data. And also all the other 11 characters. ### What other features in the dataset do you think will help support your investigation into your feature(s) of interest? Most of the observations have: 1.Quality of 5,6. Very minimum observations are seen with quality 3,7,8. 2.Average pH is over 3 and 3.5 3.Alcohol value between 9 and 11 4.very less citric acid, density, chlorides and sulphates value.
Did you create any new variables from existing variables in the dataset?
No.
Of the features you investigated, were there any unusual distributions? Did you perform any operations on the data to tidy, adjust, or change the form of the data? If so, why did you do this?
Volatile acid, chlorides,citric acid residual sugar, total sulpher dioxide, sulphates have very minimal observations as the value increases. X limits on these plots have been adjusted for better understanding.and visualization.
Bivariate Plots Section
Let us look at the correlation statistics
## fixed.acidity volatile.acidity citric.acid
## fixed.acidity 1.00000000 -0.256130895 0.67170343
## volatile.acidity -0.25613089 1.000000000 -0.55249568
## citric.acid 0.67170343 -0.552495685 1.00000000
## residual.sugar 0.11477672 0.001917882 0.14357716
## chlorides 0.09370519 0.061297772 0.20382291
## free.sulfur.dioxide -0.15379419 -0.010503827 -0.06097813
## total.sulfur.dioxide -0.11318144 0.076470005 0.03553302
## density 0.66804729 0.022026232 0.36494718
## pH -0.68297819 0.234937294 -0.54190414
## sulphates 0.18300566 -0.260986685 0.31277004
## alcohol -0.06166827 -0.202288027 0.10990325
## quality 0.12405165 -0.390557780 0.22637251
## residual.sugar chlorides free.sulfur.dioxide
## fixed.acidity 0.114776724 0.093705186 -0.153794193
## volatile.acidity 0.001917882 0.061297772 -0.010503827
## citric.acid 0.143577162 0.203822914 -0.060978129
## residual.sugar 1.000000000 0.055609535 0.187048995
## chlorides 0.055609535 1.000000000 0.005562147
## free.sulfur.dioxide 0.187048995 0.005562147 1.000000000
## total.sulfur.dioxide 0.203027882 0.047400468 0.667666450
## density 0.355283371 0.200632327 -0.021945831
## pH -0.085652422 -0.265026131 0.070377499
## sulphates 0.005527121 0.371260481 0.051657572
## alcohol 0.042075437 -0.221140545 -0.069408354
## quality 0.013731637 -0.128906560 -0.050656057
## total.sulfur.dioxide density pH
## fixed.acidity -0.11318144 0.66804729 -0.68297819
## volatile.acidity 0.07647000 0.02202623 0.23493729
## citric.acid 0.03553302 0.36494718 -0.54190414
## residual.sugar 0.20302788 0.35528337 -0.08565242
## chlorides 0.04740047 0.20063233 -0.26502613
## free.sulfur.dioxide 0.66766645 -0.02194583 0.07037750
## total.sulfur.dioxide 1.00000000 0.07126948 -0.06649456
## density 0.07126948 1.00000000 -0.34169933
## pH -0.06649456 -0.34169933 1.00000000
## sulphates 0.04294684 0.14850641 -0.19664760
## alcohol -0.20565394 -0.49617977 0.20563251
## quality -0.18510029 -0.17491923 -0.05773139
## sulphates alcohol quality
## fixed.acidity 0.183005664 -0.06166827 0.12405165
## volatile.acidity -0.260986685 -0.20228803 -0.39055778
## citric.acid 0.312770044 0.10990325 0.22637251
## residual.sugar 0.005527121 0.04207544 0.01373164
## chlorides 0.371260481 -0.22114054 -0.12890656
## free.sulfur.dioxide 0.051657572 -0.06940835 -0.05065606
## total.sulfur.dioxide 0.042946836 -0.20565394 -0.18510029
## density 0.148506412 -0.49617977 -0.17491923
## pH -0.196647602 0.20563251 -0.05773139
## sulphates 1.000000000 0.09359475 0.25139708
## alcohol 0.093594750 1.00000000 0.47616632
## quality 0.251397079 0.47616632 1.00000000Let’s examine the correlation matrix with the correlative value. We know that the correlation values range from -1 to 1, with value towards 1 are positively correlated and towards -1 is negatively correlated 
Let us draw the correlation pairs figure and observe the graphs 
When we see how quality is correlated with others, we observe the following:
## fixed.acidity volatile.acidity citric.acid residual.sugar chlorides
## [1,] 0.1240516 -0.3905578 0.2263725 0.01373164 -0.1289066
## free.sulfur.dioxide total.sulfur.dioxide density pH
## [1,] -0.05065606 -0.1851003 -0.1749192 -0.05773139
## sulphates alcohol quality
## [1,] 0.2513971 0.4761663 1We see that quality is positive correlated with alcohol,fixed acidity citric acid, residual sugar and sulphates and negatively correlated with volatile acidity, chlorides, free sulphur dioxide, total sulphur dioxide, desnity and pH. 
Let us explore other correlations.
Bivariate Analysis
We have now observed the correlation and impact of other factors on quality.
Talk about some of the relationships you observed in this part of the investigation. How did the feature(s) of interest vary with other features in the dataset?
We observe that Quality has: 1.significant positive correlation with Fixed Acidity, Citric Acid,Sulphates and Alcohol 2.No significant positive or negative relation with density and residual sugar. 3.Significant negative correlation with chlorides and volatile acidity
Did you observe any interesting relationships between the other features (not the main feature(s) of interest)?
Density and citric acidity increase with fixed acidity whole pH decreases. Total Sulphur dioxide and free sulphur dioxide are linearly positive.
What was the strongest relationship you found?
Quality increases with citric acid and decreases with volatile acidity
Multivariate Plots Section
Multivariate Analysis
Talk about some of the relationships you observed in this part of the . Were there features that strengthened each other in terms of at your feature(s) of interest?
With increase in free and total sulphur dioxe, quality increases. Quality decreases with increase in volatile acidity and fixed acidity Citric acidity increases with fixed acidity and so does quality
Were there any interesting or surprising interactions between features?
Volatile acidity decreases with increase in cirtic acidity as well as fixed acidity. Most of the high quality observations have density below 20.
Final Plots and Summary
Plot One
Description One
We see that high alcohol and low density gives good alcohol quality. ### Plot Two 
Description Two
From above we see that as total and free sulphur dioxide increaseand quality increases, but low quantities of each gives good quality.
Plot Three
Description Three
We see that increase in alcohol increases quality.
Reflection
Some analysis has been done to understand the impacting features on redwine dataquality. We understand how some features alone do not effect the quality. It is important to do a complete analysis before coming to conclusions. Some of the interesting findings made through our analysis: 1.More than 60% of data have avergae quality 2.Free and total sulphur dioxide increase parallelly but lower quantities of these ensure good quality. 3.High alcohol rate and low density increases quality.
What were some of the struggles that you went through?What went well? What was surprising? Make sure you include an insight intofuture work that could be done with the dataset
I Struggled to understand the data set and analysis what plots can make better visualization. Although initially I faced difficulty, analysis went easy once started working. Suprising is how most of the observations have average quality value and how it decreases with density. Statistical tests and analysis can be done to proove the analysis mathematically.